Poster Open Access

Characterization of the NEXT-White Detector with Calibration Data

RENNER, J.


Citation Style Language JSON Export

{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.1300767", 
  "title": "Characterization of the NEXT-White Detector with Calibration Data", 
  "issued": {
    "date-parts": [
      [
        2018, 
        6, 
        29
      ]
    ]
  }, 
  "abstract": "<p>The NEXT (Neutrino Experiment with a Xenon TPC) experiment will search for neutrinoless double-beta (<span class=\"MathJax\"><span class=\"math\"><span><span><span class=\"mrow\"><span class=\"mn\">0</span><span class=\"mi\">&nu;</span><span class=\"mi\">&beta;</span><span class=\"mi\">&beta;</span></span></span></span></span></span>\n0\\nu\\beta\\beta\n) decay in <span class=\"MathJax\"><span class=\"math\"><span><span><span class=\"mrow\"><span class=\"msubsup\"><span><span><span class=\"texatom\"><span class=\"mrow\"><span class=\"mn\">136</span></span></span></span></span></span></span></span></span></span></span>\n^{136}\nXe with a high pressure xenon gas time projection chamber (TPC). Two principle advantages of the NEXT approach are good energy resolution and topology-based event classification. We describe initial results from the first phase of the experiment, the detector NEXT-White deployed in the Canfranc Underground Laboratory in the Spanish Pyrenees, demonstrating recent progress towards sub-1% energy resolution at the <span class=\"MathJax\"><span class=\"math\"><span><span><span class=\"mrow\"><span class=\"msubsup\"><span><span><span class=\"texatom\"><span class=\"mrow\"><span class=\"mn\">136</span></span></span></span></span></span></span></span></span></span></span>\n^{136}\nXe double-beta Q-value. We also present the results of a topological analysis, using electron-positron pair events in place of the two-electron events expected from <span class=\"MathJax\"><span class=\"math\"><span><span><span class=\"mrow\"><span class=\"mn\">0</span><span class=\"mi\">&nu;</span><span class=\"mi\">&beta;</span><span class=\"mi\">&beta;</span></span></span></span></span></span>\n0\\nu\\beta\\beta\n, which demonstrates how such events can be distinguished from background (single-electron) events of the same energy through the use of deep neural networks (DNNs).</p>", 
  "author": [
    {
      "family": "RENNER, J."
    }
  ], 
  "type": "graphic", 
  "id": "1300767"
}
58
47
views
downloads
All versions This version
Views 5858
Downloads 4747
Data volume 98.4 MB98.4 MB
Unique views 5252
Unique downloads 4242

Share

Cite as